I had a similar experience at work. We used to be a TensorFlow shop. Last year we started playing around with Pytorch, only for R&D projects at first... and it

I had a similar experience at work. We used to be a TensorFlow shop. Last year we started playing around with Pytorch, only for R&D projects at first... and it felt like a breath of fresh air. Whereas TensorFlow always felt like it was designed and engineered from day one for massive scalability and deployment flexibility (at the expense of easy/fast development), Pytorch felt instantly like it was designed for easy/fast development by AI researchers who need to experiment and iterate through models as quickly as possible with as little hassle as possible. Almost overnight, we stopped tinkering and experimenting with TensorFlow. Earlier this year, after a blog post announcing the production-friendly features of Pytorch 1.0[a], we decided to switch our production systems from TensorFlow to Pytorch. So far we're happy with the decision. [a] https://pytorch.org/2018/05/02/road-to-1.0.html https://pytorch.org/2018/05/02/road-to-1.0.html